Plan

Plan

Overview

Create a short plan that a developer (or agent) can execute end-to-end: ordered tasks, acceptance checks, and a concrete verification strategy.

Workflow

1. Write the objective function:

   • goal (one sentence)
   • constraints (budget/time/compliance/latency/team capacity/etc.)
   • anti-goals (what you are explicitly not optimizing now)

2. Externalize a one-page system sketch:

   • boundary (in/out) + time horizon (near-term vs later)
   • actors + incentives
   • key flows (work/data/risk/attention)
   • top 3 constraints/bottlenecks

3. Scope the change:

   • impacted components/services
   • impacted boundaries/contracts (HTTP/gRPC/events/WS/data model)
   • what is explicitly out of scope

4. Load archobs data (required): Run archobs show all --format json to get risk scores, cluster health, and drift in one shot. Files with risk > 0.5 and clusters with leakage > 0.20 should appear earlier in the task order. Drift data (ari_prev < 0.50) flags areas to avoid broad moves in. If the artifacts do not exist, run archobs report --repo <path> --out .archobs --suggestions-provider rules and wait for it to complete before continuing. 4b. Risk Amplification (conditional — run when any high-risk files/clusters from archobs touch external dependencies or technology choices):

   intel forecast    # lifecycle phases for relevant dependencies
   

   Cross-reference matrix: See Lifecycle Decision Mapping — Plan: Risk Amplification for archobs signal x forecast signal → priority adjustment table.

5. Identify the primary risk(s) (pick 1–3): correctness, migration, partial failure, security/privacy, performance, operability.

6. Add a compact decision table (2–3 options including a no-change baseline):

   • what each option optimizes
   • what each option knowingly worsens
   • kill criteria / reversal trigger

7. Stress-test the decision (if 2+ viable approaches exist; skip for single viable approach):

   • Assumptions: What are facts vs assumptions? Which assumption is least certain — how will we validate it? Cross-reference with risk amplification from step 4b (if applicable). (attach to decision table)
   • Second-Order Effects: What happens next week / next quarter / next year? What new load, toil, coupling, or failure mode does this create? If this fails in 6-12 months, what likely caused failure? Cross-reference with risk amplification from step 4b (if applicable). (attach to decision table)
   • Opportunity Cost: What are we saying "no" to? Are we favoring this due to sunk cost, familiarity, or novelty? (attach to decision table)
   • If probe output already exists from an earlier Define-stage skill in this flow (including workflow orchestration), refine it instead of re-running.

8. Choose the minimum up-front artifacts:

   • if boundary semantics/contracts change → use spec
   • if cross-service/system pressure exists → use architecture
   • if in-process structure pressure exists → use design
   • if repeated boundary logic is likely → use platform

9. Produce an ordered task list:

   • tasks should be small, reversible, and verifiable
   • include “stop points” where you can re-check assumptions and kill criteria
   • include one quick blast-radius check (“if X degrades, what breaks next/silently?”)

10. Define measurement + verification:

    • measurement ladder: decision, 3 leading indicators, 3 lagging outcomes, instrumentation source, review ritual (owner + cadence + trigger)
    • exact commands (tests/lint/typecheck/build) if known
    • if unknown, list what you will run and ask once for preferred commands

Guardrails

• Keep the plan short (usually 5–12 tasks). Avoid “spec theater” for tiny changes.
• Every task needs an observable acceptance check (test, command output, file diff, or demo step).
• Call out unknowns early; don’t pretend certainty.
• No metric without a named decision it informs.
• For non-trivial work, include explicit opportunity costs; avoid decision-by-default.
• If you propose retries, also propose idempotency/dedupe and time budgets (resilience).

Output Template

Return:

• Goal: 1–2 sentences.
• Objective function: goal + constraints + anti-goals.
• System sketch: boundary/time horizon, actors/incentives, key flows, bottlenecks.
• Scope: in/out.
• Decision table: options, optimizations, known downsides, kill criteria, assumptions (facts vs assumptions), and opportunity costs.
• Risks/assumptions: 3–6 bullets.
• Plan: ordered checklist with acceptance per task.
• Measurement ladder: leading/lagging indicators, instrumentation, owner/cadence/trigger.
• Verification: commands to run + what “good” looks like.
• Open questions: only if blocking.

References

• Empirical risk data for prioritization: archobs
• Structured-thinking probes + templates: ../references/ (checklists for inline probes, templates for escalation)